The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Generalized quotient image
Abstract
We present a unified framework for modeling intrinsic properties of face images for recognition. It is based on the quotient image (QI) concept, in particular on the existing works of QI, spherical harmonic, image ratio and retinex. Under this framework, we generalize these previous works into two new algorithms: (1) non-point light quotient image (NPL-QI) extends QI to deal with non-point light sources by modeling non-point light directions using spherical harmonic bases; (2) self-quotient image (S-QI) extends QI to perform illumination subtraction without the need for alignment and no shadow assumption. Experimental results show that our algorithms can significantly improve the performance of face recognition under varying illumination conditions.
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Citations
Cites
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Cited by
Total variation models for variable lighting face recognition
Chen, T., Yin, W., Zhou, X. S., Comaniciu, D., & Huang, T. S. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.195 · Cited by 437
Metadata
- Authors
- Wang, H., Li, S. Z., & Wang, Y.
- Venue
- Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.
- Publisher
- IEEE
- Published
- 2004-11-12
- Volume
- 2
- Pages
- 498-505
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2156772312
- Cited by
- 170
- References
- 1
- FWCI
- 6.76
- Type
- conference paper
- Language
- en
- Open access
- closed
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- The paper
- Wang, H., Li, S. Z., & Wang, Y. (2004). Generalized quotient image. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. https://doi.org/10.1109/cvpr.2004.1315205
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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